Triple
T6728763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paso de Agua Negra |
E153581
|
entity |
| Predicate | hasDrivingConditions |
P73396
|
FINISHED |
| Object | challenging |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: challenging | Statement: [Paso de Agua Negra, hasDrivingConditions, challenging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrivingConditions Context triple: [Paso de Agua Negra, hasDrivingConditions, challenging]
-
A.
driverRequirement
Indicates that a certain driver, qualification, or driving-related condition is required for an entity to perform or be associated with a particular role, task, or operation.
-
B.
hasDriverCategory
Indicates that an entity (such as a vehicle or driving role) is associated with a specific driver category or license class.
-
C.
allowsCupDrivers
Indicates that one entity grants permission or authorization for Cup drivers to participate in or make use of another entity.
-
D.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
E.
hasLimitedRoadAccess
Indicates that an entity can only be reached by a small number of roads, restricted routes, or otherwise constrained vehicular access.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d35134148190b49fb5c25a0f8ed4 |
completed | March 27, 2026, 6:58 p.m. |
Created at: March 27, 2026, 2:08 p.m.